1. Field of the Invention
The present invention relates to a system for controlling an unmanned vehicle by detection of a guide line based on a picture image picked up by a camera on the vehicle. The system according to the present invention can be used for automatically driving an unmanned vehicle along a guide line on the ground by using detection of the guide line by processing picture data and by controlling the vehicle steering by, for example, a fuzzy inference.
2. Description of the Related Arts
In a prior art control of an unmanned vehicle by detection of a guide line based on a picture image picked up by a camera on the vehicle, the so-called parameter space method is used in which data of extracted points are obtained, parameters (.rho., .theta.) are derived from the extracted point data, the maximum density parameter is derived, and accordingly the parameters (.rho., .theta.) of the guide line are determined based on the maximum density parameter.
Of the above parameters, .rho. represents the distance of the guide line picture from the reference point in the picture plane, and .theta. represents the angle of the guide line picture from the reference line in the picture plane.
The guide line is represented by the following equation (1), where X and Y are the coordinates of an extracted point on the guide line. EQU Xcos.theta.+Ysin.theta.=.rho. (1)
In the determination of the parameter of the guide line, the .rho.- .theta. space is divided by a grid pattern into a plurality of squares, the integration of parameters is carried out for each of the squares, the density of the parameters is calculated for each of the squares, and accordingly the parameter of the guide line is determined.
However, there have been problems in the prior arts such that a great many calculations are needed for the determination of the parameter of guide line, much time is needed for the calculations, no measures are taken to counteract the variations of the vehicle motion, and the data processings are apt to be affected by the existence of noise data caused by the variations of the vehicle motion.